The role of entropy in the success of nonstoichiometric oxides for two-step thermochemical water and CO2 splitting
Bibliographic record
Abstract
Owing to their high theoretical efficiency, two-step solar thermochemical water and CO2 splitting cycles, using a metal oxide intermediate, provide a promising pathway to store solar energy in a stable chemical bond. To date, the most successful demonstrations have utilized nonstoichiometric oxides, a class of materials capable of continuously transitioning from an oxidized to reduced state via formation of oxygen vacancies. The success of nonstoichiometric oxides is typically attributed to their ability to maintain their crystallographic phase, allowing them to be cycled many times without destabilizing–a tremendous practical advantage. In this work, we utilize a combined empirical and statistical thermodynamics approach to present an alternative explanation of the success of nonstoichiometric oxides from an entropy perspective. We first illuminate the importance of the entropy change of the reduction reaction as a key material parameter. We then develop a methodology for plotting nonstoichiometric oxides on the Ellingham diagram, enabling a direct comparison to stoichiometric materials. This analysis reveals the unique ability of nonstoichiometric oxides to achieve a significant solid-state entropy contribution, which results from the disorder generated via oxygen vacancy formation. To quantify the solid-state entropy, we develop a simple configurational entropy model applicable to any oxygen-deficient nonstoichiometric oxide. We compare model predictions to existing data for two important nonstoichiometric oxides, CeO2−δ and La0.6Ca0.4Mn0.6Al0.4O3−δ, to reveal the main trends in entropy vs δ and material composition and discuss the causes and implications of deviations from the theory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".